RF resources are a finite commodity in high demand, especially in particular high demand areas where mobile device clusters tend to form, which places demands on available RF resources that often result in various network performance issues including dropped calls and unavailability to a mobile device of a wireless link.
In recent years demand for wireless voice services has either increased marginally, or in some markets levelled off. Coinciding with this trend, however, has been an exponential increase in demand for data services.
As illustrated for example in FIG. 1, each wireless network operator is licensed blocks of radio frequency spectrum for the respective operator's radio access network (“RAN”). With that in mind, at a given instant, in a given location, the operator in Block A may experience a lull in RAN demand for data services, while the operator in Block B is overwhelmed with traffic. The next moment, the reverse could be true. Afterwards, both RANs could be momentarily idle.
This dynamic is multiplied by the number of wireless operators and active bands operating in a given service area. Because of the transient, episodic nature of data communications, there is a chaotic nature to the demand for, and availability of, RF resources.
Over and above the sheer increase in demand, data sessions behave very differently from voice calls in the following ways: (i) voice is circuit switched, data is packet switched; (ii) voice is full-duplex, whereas data can be full or half duplex, or even simplex in certain applications; (iii) data sessions are based on protocols that tolerate a degree of network disruption without the application failing or closing, while a mere syllable lost in a voice call is perceptible, and unacceptable to the user; (iv) the routing of data packets is highly dynamic whereas the routing of voice sessions is rigidly predefined and predictable.
These, and other characteristics, present both challenges and opportunities in terms of mobile service radio spectrum utilization. Innovation in the domain of network performance optimization has tended to focus on various technologies or techniques implemented network by network such a bandwidth optimization.
Certain network providers have tried to address exhaustion of RAN resources in specific areas by deploying Wi-Fi Access Points (AP) as a means of offloading traffic in certain congested areas. However, there are a number of important characteristics inherent in Wi-Fi that lead to a departure from the experience a user expects from a Mobile Network Operator (MNO): (i) small coverage (originally intended for use within a home or small business); (ii) unlicensed, meaning there is no reliable way of managing interference; (iii) non-assured service quality (best effort); (iv) performance rapidly deteriorates as the number of users increases; (v) no support for mobility; (vi) unpredictable and inconvenient support for nomadic user behavior; (vii) user confusion/uncertainty with regards to whether they are on the cellular network (being charged), or Wi-Fi (no charge, but no service level assurance) at any given instant; and (viii) often impractical for the MNO to charge for Wi-Fi in macro network service areas.
Accordingly, there is a need for a new solution that provides better utilization of available network resources in a defined location.